Loss-of-function variants in CSDE1 have been strongly linked to neuropsychiatric disorders, yet the precise role of CSDE1 in neurogenesis remains elusive. In this study, we demonstrate that knockout of Csde1 during cortical development in mice results in impaired neural progenitor proliferation, leading to abnormal cortical lamination and embryonic lethality. Transcriptomic analysis revealed that Csde1 upregulates the transcription of genes involved in the cell cycle network. Applying a dual thymidine-labelling approach, we further revealed prolonged cell cycle durations of neuronal progenitors in Csde1-knockout mice, with a notable extension of the G1 phase. Intersection with CLIP-seq data demonstrated that Csde1 binds to the 3' untranslated region (UTR) of mRNA transcripts encoding cell cycle genes. Particularly, we uncovered that Csde1 directly binds to the 3' UTR of mRNA transcripts encoding Cdk6, a pivotal gene in regulating the transition from the G1 to S phases of the cell cycle, thereby maintaining its stability. Collectively, this study elucidates Csde1 as a novel regulator of Cdk6, sheds new light on its critical roles in orchestrating brain development, and underscores how mutations in Csde1 may contribute to the pathogenesis of neuropsychiatric disorders.
Animals ; Neurogenesis/genetics* ; Cell Cycle/genetics* ; Mice, Knockout ; Mice ; Neural Stem Cells/metabolism* ; DNA-Binding Proteins/metabolism* ; Cyclin-Dependent Kinase 6/genetics* ; Cell Proliferation ; 3' Untranslated Regions ; Cerebral Cortex/embryology* ; RNA-Binding Proteins ; Mice, Inbred C57BL

Objective:To evaluate lung ultrasound (LUS) for dynamic monitoring during invasive mechanical ventilation in preterm infants with neonatal respiratory distress syndrome (NRDS) and characterize LUS features before and after ventilation.Methods:This retrospective cohort study enrolled 110 NRDS preterm infants requiring invasive mechanical ventilation within 24 hours of admission at Kunming Children's Hospital from August 2019 to June 2022. Patients were divided into control ( n=61, pre-LUS era from August 2019 to May 2021) and LUS groups ( n=49, LUS era from June 2021 to June 2022). LUS manifestations before and after ventilation were systematically analyzed, with intergroup comparisons of complications (pneumothorax, pulmonary hemorrhage, pulmonary consolidation), ventilation duration, weaning proportions within specific timeframes, and weaning failure rates using two independent t-tests, rank-sum tests, Chi square tests (Fisher's exact test) with Bonferroni correction. Results:(1) Pre-ventilation LUS showed snowflake sign in 95.9% (47/49) and ground-glass opacity in 4.1% (2/49) of infants. Post-ventilation alveolar recruitment manifested as an abrupt reduction of the snowflake sign with complete resolution by 12 hours, while ground-glass opacity demonstrated an initial increase followed by gradual decrease, with subsequent emergence of A-lines after 12 hours of ventilation. (2) The LUS group showed a higher detection rate of pulmonary consolidation compared to the control group assessed by chest X-ray [65.3% (32/49) vs. 14.8% (9/61), χ2=29.70, P=0.001]. (3) The LUS group demonstrated higher weaning proportion within 24 hours [22.4% (11/49) vs. 0.0% (0/61)], and lower proportion beyond 72 hours [40.8% (20/49) vs. 67.2% (41/61)] (Bonferroni-corrected, both P<0.008). (4) Ventilation duration was significantly shorter in the LUS group [54.0 (25.0-128.5) vs. 107.5 (52.3-143.8) hours, Z=－2.85, P=0.004] with comparable weaning failure rates [10.2% (5/49) vs. 9.8% (6/61), χ2<0.01, P>0.999]. Conclusion:LUS patterns differ significantly pre- and post-ventilation in NRDS infants, enabling dynamic monitoring of pulmonary changes during mechanical ventilation to facilitate treatment adjustment and timely extubation.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

The enterotoxigenic Escherichia coli (ETEC) infection is a major factor restricting the development of animal husbandry. However, the abuse of antibiotics will lead to the antibiotic residues and emergence of antibiotic-resistant bacteria. The existing vaccines face challenges in stimulating intestinal immunity, demonstrating limited prevention effects. Therefore, it is indispensable to develop a new vaccine that is safe and suitable as a feed additive to activate intestinal immunity. This study constructed yeast-cell microcapsules (YCM) carrying the DNA vaccine against ETEC by genetic engineering. Furthermore, animal experiments were carried out to explore the regulatory effects of feeding YCM on the intestinal immune system and intestinal microbiota. Saccharomyces cerevisiae was selected as the oral delivery vehicle (microcapsules) of the DNA vaccine. The codon-optimized nucleic acid sequence of K88, the main antigen of mammal-derived ETEC, was synthesized, and the yeast shuttle vector containing the corresponding DNA vaccine expression cassette was constructed by DNA recombination. The recombinant strain of YCM was prepared by transforming JMY1. Additionally, the characteristics of the YCM strain and its feasibility as an oral vaccine were comprehensively evaluated by the fluorescence reporter assay, gastrointestinal fluid tolerance assay, intestinal epithelial cell adhesion assay, intestinal retention assessment, antiserum detection, and intestinal microbiota detection. The experimental results showed that the DNA vaccine expression cassette was expressed in mammals, and the recombinant strain of YCM could tolerate up to 8 hours of gastrointestinal fluid digestion and had good adhesion to intestinal epithelial cells. The results of mouse feeding experiments indicated that the recombinant strain of YCM could stay in the intestinal tract for at least two weeks, and the DNA vaccine expression cassette carried by YCM entered the intestinal immune system and triggered an immune response to induce the production of specific antibodies. Moreover, feeding YCM recombinant bacteria also improved the abundance of gut microbiota in mice, demonstrating a positive effect in regulating intestinal flora. In summary, we prepared the recombinant strain of YCM carrying the DNA vaccine against ETEC and comprehensively evaluated its characteristics and feasibility as an oral vaccine. Feeding the recombinant YCM could induce specific immune responses and regulate intestinal microbiota. The findings provide a reference for the immunoprevention of ETEC-related animal diseases.
Animals ; Enterotoxigenic Escherichia coli/genetics* ; Saccharomyces cerevisiae/metabolism* ; Vaccines, DNA/genetics* ; Mice ; Escherichia coli Infections/immunology* ; Escherichia coli Vaccines/genetics* ; Capsules ; Mice, Inbred BALB C ; Female

Senecavirus A (SVA) is a major viral pathogen causing disease in pigs, and effective monitoring of SVA infection is critical for disease control. In this study, we aimed to develop a reliable ELISA method for rapidly detecting neutralizing antibodies against SVA. We used HEK293F cells to express an SVA-specific porcine Fab antibody and verified the biological activity of the Fab antibody by indirect ELISA, immunofluorescence assay, virus neutralization test, and Western blotting. The Fab antibody was biotinylated and used as a competitive antibody to establish a competitive ELISA (C-ELISA) for detecting neutralizing antibodies against SVA. We then evaluated the C-ELISA in terms of sensitivity, specificity, repeatability, and result agreement rate with the VNT. The results showed that we successfully prepared an SVA-specific porcine Fab antibody, which showed high affinity for SVA. We named this antibody 1M33Fab and designated it as Bio-1M33Fab after biotin labeling. The assay conditions were optimized as follows: the coating concentration of SVA particles being 1 μg/mL, the working concentration of Bio-1M33Fab being 0.5 μg/mL, the optimal serum dilution of 1:10, and the optimal dilution of enzyme-labeled avidin being 1:30 000. At a percent inhibition (PI) of 47%, the assay demonstrated the highest sensitivity (96.88%) and specificity (100%), with no cross-reactivity observed with the positive sera of major porcine viral diseases. The intra-assay coefficient of variation ranged from 1.12% to 7.34%, while the inter-assay coefficient of variation ranged from 1.10% to 8.97%, indicating good repeatability. In the detection of 224 clinical pig serum samples, C-ELISA and VNT showed a result agreement rate of 93.75%. In conclusion, we successfully develop a C-ELISA method for detecting neutralizing antibodies against SVA by using a porcine-derived Fab antibody, which lays a foundation for the development of detection kits.
Animals ; Swine ; Antibodies, Neutralizing/immunology* ; Enzyme-Linked Immunosorbent Assay/methods* ; Immunoglobulin Fab Fragments/immunology* ; Antibodies, Viral/immunology* ; Picornaviridae/immunology* ; Humans ; HEK293 Cells ; Swine Diseases/diagnosis* ; Picornaviridae Infections/diagnosis*

Objective:To analyze the quality level of maternal mid-trimester serum prenatal screening in China from 2019 to 2023.Methods:A questionnaire survey was conducted to collect information from laboratories participating in the National Health Commission′s Clinical Laboratory Center inter-laboratory quality assessment program for prenatal screening from 2019 to 2023. The collected data included screening protocols, detection methods, testing systems, and monthly laboratory screening quality indicators. The Chi-square test was used to compare the initial screening positive rates among different screening protocols, provinces, detection methods, and testing systems. A log-transformed linear regression analysis was performed to evaluate the relationship between the average annual sample size and the out-of-control rate of various median multiple of the median (mMoM) values.Results:This study included 806 laboratories from 29 provinces (including autonomous regions and municipalities). The five-year average out-of-control rates for mMoM values across indicators ranged from 15.8% to 31.3%. The initial positive rates of dual, triple, and quadruple screening protocols were statistically different ( χ2=760.2, P<0.001). The initial positive rates across different provinces ranged from 4.7% to 10.3%, with statistically significant differences ( χ2=35 388.0, P<0.001). There were also statistically significant differences in initial positive rates between different testing systems ( χ2=2 493.2, P<0.001). Testing systems using chemiluminescence methods had significantly higher initial positive rates compared to systems using time-resolved fluorescence methods (7.2% vs. 6.5%, χ2=533.6, P<0.001). Log-linear regression analysis showed that testing systems with larger annual average sample sizes had lower out-of-control rates for mMoM values (AFP: β=-0.100, P=0.005; hCG: β=-0.123, P=0.008; uE3: β=-0.139, P=0.007). Conclusion:There are significant differences in the quality of maternal mid-trimester serum screening across different detection methods, testing systems and provinces in China.

OBJECTIVES: To investigate the effects of methylenetetrahydrofolate reductase (MTHFR) rs1801133 and γ-glutamyl hydrolase (GGH) rs11545078 gene polymorphisms on plasma concentrations and toxicity following high-dose methotrexate (MTX) therapy in children with acute lymphoblastic leukemia (ALL). METHODS: Children with ALL treated at the Xuzhou Children's Hospital of Xuzhou Medical University from January 2021 to April 2024 were selected for this study. Genotypes of MTHFR rs1801133 and GGH rs11545078 were determined using multiplex polymerase chain reaction. MTX plasma concentrations were measured by enzyme-multiplied immunoassay technique, and toxicity was graded according to the Common Terminology Criteria for Adverse Events version 5.0. The relationships between MTHFR rs1801133 and GGH rs11545078 genotypes and both MTX plasma concentrations and associated toxicities were analyzed. RESULTS: In the low-risk ALL group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 72 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05), and the GGH rs11545078 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with the occurrence of reduced hemoglobin (P<0.05), and the GGH rs11545078 genotype was associated with the occurrence of thrombocytopenia (P<0.05). CONCLUSIONS Detection of MTHFR rs1801133 and GGH rs11545078 genotypes can be used to predict increased MTX plasma concentrations and the occurrence of toxic reactions in high-dose MTX treatment of ALL, enabling timely interventions to enhance safety.
Humans ; Methotrexate/toxicity* ; Methylenetetrahydrofolate Reductase (NADPH2)/genetics* ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/blood* ; Male ; Female ; Child ; Child, Preschool ; gamma-Glutamyl Hydrolase/genetics* ; Antimetabolites, Antineoplastic/adverse effects* ; Infant ; Polymorphism, Genetic ; Adolescent ; Genotype ; Polymorphism, Single Nucleotide

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Cuproptosis, a recently identified form of regulated cell death triggered by excess intracellular copper, has emerged as a promising cytotoxic strategy for cancer therapy. However, the therapeutic efficacy of copper ionophores such as elesclomol (ES) is often hindered by cellular copper homeostasis mechanisms that limit copper influx and cuproptosis induction. To address this challenge, we developed a nanoagent utilizing outer membrane vesicle (OMV) derived from Akkermansia muciniphila (Akk) for co-delivery of antioxidant 1 copper chaperone (Atox1)-targeting siRNA and ES (siAtox1/ES@OMV) to tumors. In vitro, we demonstrated that Atox1 knockdown via siRNA significantly disrupted copper export mechanisms, resulting in elevated intracellular copper levels. Simultaneously, ES facilitated efficient copper influx and mitochondrial transport, leading to Fe-S cluster depletion, increased proteotoxic stress, and robust cuproptosis. In vivo, siAtox1/ES@OMV achieved targeted tumor delivery and induced pronounced cuproptosis. Furthermore, leveraging the immunomodulatory properties of OMVs, siAtox1/ES@OMV promoted T-cell infiltration and the activation of tumor-reactive cytotoxic T cells, enhancing tumor immune responses. The combination of siAtox1/ES-induced cuproptosis and immunogenic cell death synergistically suppressed tumor growth in both subcutaneous breast cancer and orthotopic rectal cancer mouse models. This study highlights the potential of integrating copper homeostasis disruption with a copper ionophore using an immunomodulatory OMV-based vector, offering a promising combinatorial strategy for cancer therapy.